With the distributed generation technology widely applied, some system problems such as overvoltages and undervoltages are gradually remarkable, which are caused by distributed generations like wind energy system (WES) and photovoltaic system (PVS) because of their probabilistic output power which relied on natural conditions. Since the impacts of WES and PVS are important in the distribution system voltage quality, we study these in this paper using new models with the probability density function of node voltage and the cumulative distribution function of total losses. We apply these models to solve the IEEE33 distribution system to be chosen in IEEE standard database. We compare our method with the Monte Carlo simulation method in three different cases, respectively. In the three cases, these results not only can provide the important reference information for the next stage optimization design, system reliability, and safety analysis but also can reduce amount of calculation.

Overhead transmission line icing is one of the main factors affecting safety and reliability of power grid. This paper proposed an excitation deicing method of iced wire and theoretically revealed the ice removal mechanism under displacement excitation conditions, by taking the LGJ-70/10 glaze icing wire as the 3D model and analyzing and studying its dynamic response under the effect of displacement excitation. The simulation results show that the stress of wire icing area is enlarged with the increase of excitation displacement and frequency. Through the comparison of the compression strength experimental results on a series of different iced wires in low temperature environment, the authors found out that the stress generated from the wire icing area is greater than the crushing strength of the ice within the scope of the calculation parameters, which proved the validity and the feasibility of the method, and finally the suitable excitation displacement is determined. Following studies show that, as far as possible, it is necessary to reduce the incentive displacement and also to select the appropriate constraint length in order to avoid the line jumping that may be caused by large span ice shedding.

A new type of photovoltaic grid power generation system control scheme to solve the problems of the conventional photovoltaic grid power generation systems is presented. To aim at the oscillation and misjudgment of traditional perturbation observation method, an improved perturbation observation method comparing to the next moment power is proposed, combining with BOOST step-up circuit to realize the maximum power tracking. To counter the harmonic pollution problem in photovoltaic grid power generation system, the deadbeat control scheme in fundamental wave synchronous frequency rotating coordinate system of power grid is presented. A parameter optimization scheme based on positive feedback of active frequency shift island detection to solve the problems like the nondetection zone due to the import of disturbance in traditional island detection method is proposed. Finally, the results in simulation environment by MATLAB/Simulink simulation and experiment environment verify the validity and superiority of the proposed scheme.

In order to implement a high-efficiency bridgeless power factor correction converter, a new topology and operation principles of continuous conduction mode (CCM) and DC steady-state character of the converter are analyzed, which show that the converter not only has bipolar-gain characteristic but also has the same characteristic as the traditional Boost converter, while the voltage transfer ratio is not related with the resonant branch parameters and switching frequency. Based on the above topology, a novel bridgeless Bipolar-Gain Pseudo-Boost PFC converter is proposed. With this converter, the diode rectifier bridge of traditional AC-DC converter is eliminated, and zero-current switching of fast recovery diode is achieved. Thus, the efficiency is improved. Next, we also propose the one-cycle control policy of this converter. Finally, experiments are provided to verify the accuracy and feasibility of the proposed converter.

An investigation on qualitative dynamics in a voltage-current dual-loop controlled flywheel energy storage system (FESS) operating in discharge mode is presented in this paper, providing novel insights into the effect of two-timescale characteristics on the safety and stability of energy transmission of FESS. Based on singular perturbation theory, a two-timescale approach is proposed to separate the FESS into the fast and slow subsystems. Stability analysis of the transient fixed points confirms the effects of systemic parameters on FESS’s dynamics and indicates that the FESS shifts from the spiking state to the quiescent state when the slow variable crosses the bifurcation point of the fast subsystem. Mechanism analysis reveals that the root cause of the qualitative dynamics is the voltage instability of the FESS. Moreover, the feasibility boundaries of key parameters are derived, and application requirements of the proposed approach are also discussed, guiding the extension of the approach to engineering applications and solving the dynamics analysis problem to some extent at a theoretical analysis level. Constant voltage discharge experiment is performed based on the FESS test bench built in Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, which validates the theoretical results.

As an important tool of transmission system dispatching, the region-based method has just been introduced into distribution area with the ongoing smart distribution grid initiatives. First, a more accurate distribution system security region (DSSR) model is proposed. The proposed model is based on detailed feeder-interconnected topology, and both substation transformer and feeder N-1 contingencies are considered. Second, generic characteristics of DSSR are discussed and mathematically proved. That is, DSSR is a dense set of which boundary has no suspension and can be expressed by several union subsurfaces. Finally, the results from both a test case and a practical case demonstrate the effectiveness of the proposed modeling approach; the shape of DSSR is also illustrated by means of 2- and 3-dimensional visualization. Moreover, the DSSR-based assessment and control are preliminary illustrated to show the application of DSSR. The researches in this paper are fundamental work to develop new security region theory for future distribution systems.

An intuitive model is proposed in this paper to describe the electrical behavior of certain ultracapacitors. The model is based on a simple expression that can be fully characterized by five real numbers. In this paper, the measured impedances of three ultracapacitors as a function of frequency are compared to model results. There is good agreement between the model and measurements. Results presented in a previous study are also reviewed and the paper demonstrates that those results are also consistent with the newly described model.

Electric vehicles (EVs) are developing remarkably fast these years which makes the technology of vehicle-to-grid (V2G) easier to implement. Peak load shifting (PLS) is an important part of V2G service. A model of EVs’ capacity in V2G service is proposed for the research on PLS in this paper. The capacity is valued in accordance with three types of situations. Based on the model, three different scenarios are suggested in order to evaluate the capacity with MATLAB. The evaluation results indicate that EVs can provide potential energy to participate in PLS. Then, the principle of PLS with EVs is researched through the analysis of the relationship between their power and capacity. The performance of EVs in PLS is also simulated. The comparison of two simulation results shows that EVs can fulfill the request of PLS without intensely lowering their capacity level.

To accurately forecast energy consumption plays a vital part in rational energy planning formulation for a country. This study applies individual models (BP, GM (1, 1), triple exponential smoothing model, and polynomial trend extrapolation model) and combination forecasting models to predict China’s energy consumption. Since area correlation degree (ACD) can comprehensively evaluate both the correlation and fitting error of forecasting model, it is more effective to evaluate the performance of forecasting model. Firstly, the forecasting model’s performances rank in line with ACD. Then ACD is firstly proposed to choose individual models for combination and determine combination weight in this paper. Forecast results show that combination models usually have more accurate forecasting performance than individual models. The new method based on ACD shows its superiority in determining combination weights, compared with some other combination weight assignment methods such as: entropy weight method, reciprocal of mean absolute percentage error weight method, and optimal method of absolute percentage error minimization. By using combination forecasting model based on ACD, China’s energy consumption will be up to 5.7988 billion tons of standard coal in 2018.

In order to detect islanding nondestructively, an islanding detection method for microgrid is proposed based on adaptive and periodic disturbance on the reactive power output of inverter-based distributed generation (DG). The first two parts of the disturbance in a cycle form a symmetric triangular shape and the disturbance can adaptively adjust its peak value and cycle time for two purposes. One is to minimize the total amount of the disturbance. The other is to guarantee that the absolute value of the rate of change of frequency (ROCOF) is constant during islanding, which can be utilized to be a criterion to detect islanding. The method can be applied on the DG either operating at a unity power factor or generating both active and reactive power simultaneously. Moreover, it helps to avoid the serious transient process during control strategy transformation of the DG for microgrid islanded operation. According to the anti-islanding test system in the IEEE Std. 929-2000 and IEEE Std. 1547-2003, several study cases are carried out in the PSCAD/EMTDC environment. The simulation results show that the proposed method can detect islanding rapidly and nondestructively. Moreover, it also performs effectively for the system with multiple DGs.

Fast and elitist nondominated sorting generic algorithm (NSGA2) is an improved multiobjective genetic algorithm with good convergence and robustness. The Pareto optimal solution set using NSGA2 has the character of uniform distribution. This paper builds a time-of-use (TOU) pricing mathematical model considering actual constraint conditions and puts forward a new method which realizes multiobjective TOU pricing optimization using NSGA2. A variety of objective TOU pricing schemes can be provided for decision makers compared with traditional method. Furthermore, the multiple attribute decision making theory is applied in processing the Pareto optimal solution set to calculate the optimal compromise price scheme. The simulation results have shown that the TOU pricing scheme determined by the method proposed above can achieve a better effect of clipping the peak load to fill the valley load. Consequently, the study in this paper is innovative and is a successful exploration of coordinating the relation of various objective functions concerned in TOU pricing optimization problem.

A new fault diagnosis method is proposed for PV arrays with SP connection in this study, the advantages of which are that it would minimize the number of sensors needed and that the accuracy and anti-interference ability are improved with the introduction of fuzzy group decision-making theory. We considered five “decision makers” contributing to the diagnosis of PV array faults, including voltage, current, environmental temperature, panel temperature, and solar illumination. The accuracy and reliability of the proposed method were verified experimentally, and the possible factors contributing to diagnosis deviation were analyzed, based on which solutions were suggested to reduce or eliminate errors in aspects of hardware and software.

One type of bifurcation named oscillation emergence bifurcation (OEB) found in time-delayed linear time invariant (abbr. LTI) systems is fully studied. The definition of OEB is initially put forward according to the eigenvalue variation. It is revealed that a real eigenvalue splits into a pair of conjugated complex eigenvalues when an OEB occurs, which means the number of the system eigenvalues will increase by one and a new oscillation mode will emerge. Next, a method to determine OEB bifurcation in the time-delayed LTI system with single lag is developed based on Lambert W function. A one-dimensional (1-dim) time-delayed system is firstly employed to explain the mechanism of OEB bifurcation. Then, methods to determine the OEB bifurcation in 1-dim, 2-dim, and high-dimension time-delayed LTI systems are derived. Finally, simulation results validate the correctness and effectiveness of the presented method. Since OEB bifurcation occurs with a new oscillation mode emerging, work of this paper is useful to explore the complex phenomena and the stability of time-delayed dynamic systems.

In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. A modified epsilon multiobjective evolutionary algorithm is used to solve the above model and a well-distributed Pareto front is achieved, and then the final planning scheme can be obtained from the set of nondominated solutions by a fuzzy satisfied method. The proposed method only needs the first four statistical moments and correlation coefficients of the output power of wind farms as input information; the modeling of wind power is more precise by considering the correlation between wind farms, and it can be easily combined with the multiobjective transmission network planning model. Besides, as the self-adaptive probabilities of crossover and mutation are adopted, the global search capabilities of the proposed algorithm can be significantly improved while the probability of being stuck in the local optimum is effectively reduced. The accuracy and efficiency of the proposed method are validated by IEEE 24 as well as a real system.

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

The purpose of this paper is to investigate the short-term wind power forecasting. STWPF is a typically complex issue, because it is affected by many factors such as wind speed, wind direction, and humidity. This paper attempts to provide a reference strategy for STWPF and to solve the problems in existence. The two main contributions of this paper are as follows. (1) In data preprocessing, each encountered problem of employed real data such as irrelevant, outliers, missing value, and noisy data has been taken into account, the corresponding reasonable processing has been given, and the input variable selection and order estimation are investigated by Partial least squares technique. (2) STWPF is investigated by multiscale support vector regression (SVR) technique, and the parameters associated with SVR are optimized based on Grid-search method. In order to investigate the performance of proposed strategy, forecasting results comparison between two different forecasting models, multiscale SVR and multilayer perceptron neural network applied for power forecasts, are presented. In addition, the error evaluation demonstrates that the multiscale SVR is a robust, precise, and effective approach.

DC distribution system has advantages of high power quality, large transmission capacity, high reliability, simple structure, economy and low energy consumption, and so forth. It has been a key part of smart grid nowadays. However, the development of DC distribution system is constrained by the lack of operational experience in DC system, the small interrupting capacity of DC circuit breaker (CB), and the lack of protection schemes for system itself. In this paper, protection for DC distribution system with distributed generator (DG) is fully investigated and verified. Firstly, the electromagnetic transient model of DC distribution system with DG is presented. Simulation based on the electromagnetic transient model is carried out. Both the step response and the steady-state performance verify the accuracy of the model. Then the fault characteristic mechanism is analyzed, and the protection principles and scheme are investigated in detail, including voltage mutation principle as protection starting component, differential current protection principle for DC bus, and two-section current protection for distribution lines. Finally, transient responses with protection scheme are analyzed during faults. The results present that the protection principles and scheme are feasible for DC distribution system with DG.

The power supply mode of island microgrid with a variety of complementary energy resources is one of the most effective ways to solve the problem of future island power supply. Based on the characteristics of seawater desalination system and water demand of island residents, a power allocation strategy for seawater desalination load, storage batteries, and diesel generators is proposed with the overall consideration of the economic and environmental benefits of system operation. Furthermore, a multiobjective optimal operation model for the island microgrid with wind/photovoltaic/diesel/storage and seawater desalination load is also proposed. It first establishes the objective functions which include the life loss of storage batteries and the fuel cost of diesel generators. Finally, the model is solved by the nondominated sorting genetic algorithm (NSGA-II). The island microgrid in a certain district is taken as an example to verify the effectiveness of the proposed optimal method. The results provide the theoretical and technical basis for the optimal operation of island microgrid.

With the development of wind power technology, the security of the power system, power quality, and stable operation will meet new challenges. So, in this paper, we propose a recently developed machine learning technique, relevance vector machine (RVM), for day-ahead wind speed forecasting. We combine Gaussian kernel function and polynomial kernel function to get mixed kernel for RVM. Then, RVM is compared with back propagation neural network (BP) and support vector machine (SVM) for wind speed forecasting in four seasons in precision and velocity; the forecast results demonstrate that the proposed method is reasonable and effective.

During the last few years generation from renewable energy sources (RESs) has grown considerably in European electrical networks. Transmission system operators are greatly concerned about the impact of RESs on the operational security and efficiency of their networks and more in general of the ENTSO-E interconnected system. Grid codes are to be revised in order to harmonise the rules regarding the connection of RES power plants. A main issue concerns frequency control: frequency is greatly affected by RESs intermittency and its deviations must be limited as much as possible in order to guarantee a suitable level of power quality. To improve frequency stability, in the future, Grid codes could extend frequency control requirements also to RES units, whereas today they are applied only to conventional power plants. Energy storage systems can be a possible solution to increase the flexibility and performance of RES power plants: they allow generators to modulate their power injections without wasting renewable energy. In this paper, the authors studied the suitability of extending frequency control to RES units integrating them with energy storage systems. In particular, the paper focuses on the impact of frequency control on the storage lifetime by analysing the power charge/discharge in response to real frequency oscillations.

A microgrid with low-voltage ride-through capability is designed. The designed microgrid avoids operating in unplanned islanded mode during an asymmetric ground fault which occurs in the low voltage distribution network and supports fault recovery for distribution network. Furthermore, compared with the traditional microgrid topology, the proposed microgrid topology also saves a lot of power electronic devices. The simulation results with PSCAD/EMTDC show that the microgrid can keep the distributed generations and loads operate normally when an asymmetric ground fault occurs in the low voltage distribution grid. It can also increase the active power output according to the requirement of the distribution network to support the distribution network fault recovery.

Constructing core backbone grid is conducive to strengthen the construction of grid structure and improve the ability of withstanding natural disasters. The survivability index of power grid is made up of four indices, namely, the resistibility, recoverability, security, and connectivity. Based on survivability, a method of constructing core backbone grid with the optimal criteria of the minimal total line length and the largest integrated survivability index is put forward. The biogeography-based optimization (BBO) algorithm is used to search for the core backbone grid. Compared with the traditional algorithms, BBO algorithm shows advantages in fast speed of convergence and high convergence precision. Moreover, the searching results for three kinds of objective functions by BBO algorithm verify the effectiveness of the proposed model of constructing core backbone grid.

Traditional distributed generators (DGs) planning methods take network loss minimization as the main objective to optimize DG sites in feeders. The use of load supply capability (LSC) in DG planning will precisely answer the questions how many DGs should be integrated, which transformer they should be connected to, and which type of DGs should be adopted. The main work of this paper is to analyze the impact of DGs on LSC so as to answer the three key questions. It resolves the planning problem through three steps: (i) two LSC models considering DGs’ access are developed, in which two different transfer strategies are considered: direct load transfer and indirect load transfer; (ii) the method of combined simple method and point estimate method is proposed. At last, based on a base case, when the configuration of DGs is changing, the impact of DGs on system LSC is studied. After the case study, the conclusion concerning the impact of load transfer strategy, DG capacities, and DG types on LSC is reached.

The frequency characteristic of electric equipment should be considered in the digital simulation of power systems. The traditional asynchronous machine third-order transient model excludes not only the stator transient but also the frequency characteristics, thus decreasing the application sphere of the model and resulting in a large error under some special conditions. Based on the physical equivalent circuit and Park model for asynchronous machines, this study proposes a novel asynchronous third-order transient machine model with consideration of the frequency characteristic. In the new definitions of variables, the voltages behind the reactance are redefined as the linear equation of flux linkage. In this way, the rotor voltage equation is not associated with the derivative terms of frequency. However, the derivative terms of frequency should not always be ignored in the application of the traditional third-order transient model. Compared with the traditional third-order transient model, the novel simplified third-order transient model with consideration of the frequency characteristic is more accurate without increasing the order and complexity. Simulation results show that the novel third-order transient model for the asynchronous machine is suitable and effective and is more accurate than the widely used traditional simplified third-order transient model under some special conditions with drastic frequency fluctuations.

In this paper we have treated the reliability assessment problem of low and high DG penetration level of active distribution system using the Monte Carlo simulation method. The problem is formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation. The load shedding strategy and the simulation process were introduced in detail during each FMEA process. Results indicate that the integration of DG can improve the reliability of the system if the system was operated actively.

The objective of security analysis is to find the weak link of distribution network. The $K(N-1+k)$ criterion based on the characteristics of distribution network was proposed for distribution network security analysis. According to the $K(N-1+k)$ criterion, the electrical devices in the contingency set can be classified into two kinds. The first kind meets the requirement of the $K(N-1+k)$ criterion. The rank preference optimal ordering (RPOO) was proposed to evaluate the damage degree of power system. The second kind does not meet the requirement of the $K(N-1+k)$ criterion, and it is the weak link of distribution network. A numerical experiment shows that the method is efficient and feasible, and the proposed method can provide assistant decision-making for safety precautions.

Asset management of distribution systems is an important issue for smart grid. Maintenance scheduling, as an important part of asset management, affects the reliability of distribution equipment and power supply. This research focuses on long-term distribution system maintenance scheduling aided by available operation information, which is a prominent advantage of smart grid over conventional distribution systems. In this paper, the historical and future operation information in smart grid is taken into account through a decoupled time-varying reliability model of equipment. Based on distribution system reliability assessment, a maintenance scheduling model is proposed to determine the optimal implementation time of maintenance activities to minimize distribution systems’ total cost, while satisfying reliability requirements. A combined algorithm that consists of particle swarm optimization and tabu search is designed and applied to the optimization problem. Numerical result verifies that the proposed method can schedule long-term maintenance of distribution systems in smart grid economically and effectively.

Considering the disadvantages of the traditional high-gain DC-DC converter such as big size, high voltage stress of switches, and large input current ripple, a novel high-gain interleaved boost converter with coupled-inductor and switched-capacitor was proposed correspondingly and the operation principle together with the steady-state analysis of this converter was also described. Besides, a new control approach-dynamic sliding mode evolution PWM controller (DSME PWM) for the novel topological converter based on both dynamic evolution and sliding mode control was also presented. From the simulation results and experimental validation the proposed converter can fulfill high-gain boost, low ripple of both the input current and the output voltage. Furthermore, MPPT technique can be also achieved in a short time by simulation. The efficiency and stability of the converter proposed in this paper can be improved.

Islanding detection is essential for secure and reliable operation of microgrids. Considering the relationship between the power generation and the load in microgrids, frequency may vary with time when islanding occurs. As a common approach, frequency measurement is widely used to detect islanding condition. In this paper, a novel frequency calculation algorithm based on extended Kalman filter was proposed to track dynamic frequency of the microgrid. Taylor series expansion was introduced to solve nonlinear state equations. In addition, a typical microgrid model was built using MATLAB/SIMULINK. Simulation results demonstrated that the proposed algorithm achieved great stability and strong robustness in of tracking dynamic frequency.

The increasing penetration of distributed generation resources demands better economic performance of microgrids under the smart-grid era. In this paper, a comprehensive environmental-economic dispatch method for smart microgrids is proposed, with the objective for minimizing the summation of generation and emission costs in the system. As the proposed model belongs to a large-scale nonlinear and nonconvex programming problem, a hybrid heuristic algorithm, named variable step-size chaotic fuzzy quantum genetic algorithm (VSS_QGA), is developed. The algorithm utilizes complementarity among multiple techniques including the variable step size optimization, the rotation mutational angle fuzzy control, and the quantum genetic algorithm and combines them so as to solve problems with superior accuracy and efficiency. The effectiveness of the proposed model is demonstrated through a case study on an actual microgrid system and the advantages in the performance of VSS_QGA is also verified through the comparison with genetic algorithm (GA), the evolutionary programming approach (EP), the quantum genetic algorithm (QGA), and the chaotic quantum genetic algorithm (CQGA).

Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO) algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC). The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.

Nowadays, low frequency oscillation has become a major problem threatening the security of large-scale interconnected power systems. According to generation mechanism, active power oscillation of electric power systems can be classified into two categories: free oscillation and forced oscillation. The former results from poor or negative damping ratio of power system and external periodic disturbance may lead to the latter. Thus control strategies to suppress the oscillations are totally different. Distinction from each other of those two different kinds of power oscillations becomes a precondition for suppressing the oscillations with proper measures. This paper proposes a practical approach for power oscillation classification by identifying real-time power oscillation curves. Hilbert transform is employed to obtain envelope curves of the power oscillation curves. Twenty sampling points of the envelope curve are selected as the feature matrices to train and test the supporting vector machine (SVM). The tests on the 16-machine 68-bus benchmark power system and a real power system in China indicate that the proposed oscillation classification method is of high precision.

Substation locating and sizing is an important component of urban power networks. In this paper, an improved method based on the weighted Voronoi diagram and transportation model for substation planning is proposed, which can optimize the location, capacity, and power supply range for each substation with the minimum investment which contains the cost of the lines, substations, and annual operation expense. The weighted Voronoi diagram (WVD) whose weights can be adaptively adjusted can calculate the location and the capacity for each substation with good performance of global convergence and better convergence speed. Transportation model can simulate the best correspondence relationship between the loads and substations. The impact of geographical factors is also considered in this paper. Large amount of experiments show that the improved method can get more reasonable and more optimized planning result within shorter time than the original WVD and other algorithms.

In order to improve the application area and the prediction accuracy of GM(1,1) model, a novel Grey model is proposed in this paper. To remedy the defects about the applications of traditional Grey model and buffer operators in medium- and long-term forecasting, a Variable Weights Buffer Grey model is proposed. The proposed model integrates the variable weights buffer operator with the background value optimized GM(1,1) model to implement dynamic preprocessing of original data. Taking the maximum degree of Grey incidence between fitting value and actual value as objective function, then the optimal buffer factor is chosen, which can improve forecasting precision, make forecasting results embodying the internal trend of original data to the maximum extent, and improve the stability of the prediction. To verify the effectiveness of the proposed model, the energy consumption in China from 2002 to 2009 is used for the modeling to forecast the energy consumption in China from 2010 to 2020, and the forecasting results prove that the GVGM(1,1) model has remarkably improved the forecasting ability of medium- and long-term energy consumption in China.

Recently, a password authentication and update scheme has been presented by Islam and Biswas to remove the security weaknesses in Lin and Huang’s scheme. Unfortunately, He et al., Wang et al., and Li have found out that Islam and Biswas’ improvement was vulnerable to offline password guessing attack, stolen verifier attack, privilege insider attack, and denial of service attack. In this paper, we further analyze Islam and Biswas’ scheme and demonstrate that their scheme cannot resist password compromise impersonation attack. In order to remedy the weaknesses mentioned above, we propose an improved anonymous remote authentication scheme using smart card without using bilinear paring computation. In addition, the verifier tables are no longer existent, and the privacy of users could be protected better. Furthermore, our proposal not only inherits the advantages in Islam and Biswas’ scheme, but also provides more features, including preserving user anonymity, supporting offline password change, revocation, reregistration with the same identifier, and system update. Finally, we compare our enhancement with related works to illustrate that the improvement is more secure and robust, while maintaining low performance cost.

Reasonable and strong structure is an important foundation for the smart transmission grid. For vigorously promoting construction of the smart grid, it is of great significance to have a thorough understanding of the complex structural characteristics of the power grid. The structural characteristics of several actual large-scale power grids of China are studied in this paper based on the complex network theory. Firstly, the topology-based network model of power grid is recalled for analyzing the statistical characteristic parameters. The result demonstrated that although some statistical characteristic parameters could reflect the topological characteristics of power grid from different ways, they have certain limitation in representing the electrical characteristics of power grid. Subsequently, the network model based on the electrical distance is established considering the limitation of topology-based model, which reflects that current and voltage distribution in the power grid are subject to Ohm's Law and Kirchhoff's Law. Comparing with the topology-based model, the electrical distance-based model performs better in reflecting the natural electrical characteristic structure of power grid, especially intuitive and effective in analyzing clustering characteristics and agglomeration characteristics of power grid. These two models could complement each other.

At present, the conversion efficiency of commercial small wind grid inverter is low, and, in case of low wind speed, the wind energy cannot be used efficiently. In order to resolve this problem, it is necessary to improve the topological structure and control strategy, and design a new small wind grid inverter. In this paper, we apply a two-voltage stage topology with boost converter. The boost circuit is to achieve the maximum power output of the wind energy by the segmented regulation, while the improved inverter topology realizes the overall system function with the former stage circuit. The experimental results show that the new wind grid inverter has superior performance in the low wind speed, and has the high quality energy output. This research has an important practical significance to improve the utilization of renewable energy.

An accurate estimation of the state of charge (SOC) of the battery is of great significance for safe and efficient energy utilization of electric vehicles. Given the nonlinear dynamic system of the lithium-ion battery, the parameters of the second-order RC equivalent circuit model were calibrated and optimized using a nonlinear least squares algorithm in the Simulink parameter estimation toolbox. A comparison was made between this finite difference extended Kalman filter (FDEKF) and the standard extended Kalman filter in the SOC estimation. The results show that the model can essentially predict the dynamic voltage behavior of the lithium-ion battery, and the FDEKF algorithm can maintain good accuracy in the estimation process and has strong robustness against modeling error.

This paper proposes a scheduling strategy based on real-time pricing in smart grids. A hierarchical game is employed to analyze the decision-making process of generators and consumers. We prove the existence and uniqueness of Nash equilibrium and utilize a backward induction method to obtain the generation and consumption strategies. Then, we propose two dynamic algorithms for the generators and consumers to search for the equilibrium in a distributed fashion. Simulation results demonstrate that the proposed scheduling strategy can match supply with demand and shift load away from peak time.